Documents are used to gain access to a wide variety of services and information. Included among these documents, hereinafter referred to as transaction documents, are credit cards, passports, checks, and drivers licenses. Assuring that authorized people are granted access, while denying others has significant importance in the course of daily commerce. Since these documents can be valuable, there is a great temptation to create forged or fraudulent copies. There are a large number of approaches to produce fraudulent documents, and many do not require forgery, but simply modifying machine-readable data that many of these documents carry. For instance, copying the data from a stolen credit card onto the magnetic stripe of another credit card does not require credit card forgery, but can permit unauthorized use of credit services.
In many cases, access to services requires, not only permission from a person granting services, e.g., a clerk, but also a remote facility. It is common for a credit card purchase to be remotely authorized through an electronic authorization step. A similar process occurs at many establishments for authorizing checks. A large volume of potential fraud is eliminated with these procedures.
There are numerous technologies and features available for documents to reduce the potential of forgery. These include features such as specialized overcoats, directional inks, safety paper, and holograms to name a few. Many of these permit a trained individual to determine readily if a document is forged. However, many people, such as store clerks, are not trained to perform this task. Simple-to-use methods are needed to alert a clerk that a transaction document is likely to be fraudulent. Moreover, the techniques also need to operate quickly, in order not to slow the completion of the transaction, as the vast majority of transactions are legitimate.
The use of portrait style images of the authorized document holder on transaction documents is typical. Portrait images are included on all drivers licenses within the United States and portrait images are part of all passports. Even some credit card issuers offer this feature. Many of these documents have machine-readable areas. For instance, credit cards have a magnetic stripe, some drivers licenses have two-dimensional bar-codes and so-called smart cards have an integrated circuit with memory to name but a few. A compressed image of the authorized cardholder can be stored within these areas. These machine-readable areas all have sufficient data area to store a compressed version of the portrait image of the authorized document holder. Most times, the encoded data is simply used as a means of confirming that the document has not been tampered. If the decoded image matches the image on the document, as well as a strong likeness of the person presenting the transaction document, then the document is accepted.
One aspect of many transaction verification systems is that the network used for remote verifications has many nodes and uses a relatively slow speed communications system. The ability to transmit even moderate amounts of data is unacceptable. Even a modest increase in the data required to perform a remote authorization can have serious ramifications to the overall processing time. Communication between a point of transaction and the remote facility should require a limited amount of data.
A feature of the present invention is the use of permutations. It is well known that, given an ordered list of objects, a permutation is a rearrangement of the ordering. If one considers the set of all possible permutations of n objects, it is well known that the set forms an algebraic structure commonly referred to as a group (see Serge Lang, Algebra, Addison-Wesley Publishing Company, Reading, Mass., 1965, pp. 9–13.) Begin with a standard or preferred ordering of the objects, this ordering will be referred to as the identity permutation. When this permutation is applied to the list, the resulting list is identical to the initial list. Suppose σ is another permutation, then there is another permutation σ−1, and the property is that if the permutation s followed by the permutation σ−1, then the original list is recovered. It is also important to note that if σn is a permutation that is obtained by applying the permutation n separate times, that (σ−1)n=σ−n is its inverse.
There have been implementations of transaction security systems that have a human making a decision whether the document holder and the image of the document holder match. While it is commonly accepted that humans outperform any automatic-face-verification systems built to date, there is often a reluctance to impose a human as a decision point. As an example, a young store clerk might not wish to be the critical decision point when confronted by a physically dominating thief. A means to circumvent this is to have a machine make the decision. A means of performing this decision is by a face detection algorithm as part of the transaction processing system. Consequently, another feature of the present invention is the use of face detection.
Face detection should not be confused with face recognition, as face detection refers to the ability of a computer to identify the presence and location of a human face within an image. Whereas, face recognition has the task of identifying the name of the person whose face is displayed. There are many face detection algorithms that could be utilized for this purpose, (see Erik Hjelmas and Boom Kee Low, “Face Detection: A Survey,” Computer Vision and Image Understanding, Volume 83, Number 3, September, 2001, pp. 236–274 and M-S. Yang, D. J. Kreigman, and N. Ahuja, “Detecting Faces in Images: A Survey,” IEEE Transactions in Pattern Analysis and Machine Intelligence, Volume 24, Number 1, January, 2002, pp. 34–58). These algorithms have different performance capabilities and are based upon various assumptions. Typical assumptions are that the face is face forward and oriented in the upright position. For the present invention these are easily complied with. A more important criteria for the present invention is processing speed and the rate of false negatives. Current face detection algorithms can attain satisfactory performances in both regards. However, the invention is not dependent upon the particular face detection algorithm, and as improved algorithms emerge, they can be readily deployed within the scope of the present invention.